We will use multiparameter-based indexed cell sorting, image analysis, and hierachial data analysis to identify flow cytometric probes for cell function. In this approach, the cells to be studied are processed through a multiparameter cell sorter where multiple cytometric properties are measured for each cell. The cells are then deposited in known locations on surfaces for functional analysis (e.g., colony formation). Functionally-competent cells are then scored by a quantitative microscopy system and coordinated with the cytometric parameters which described the cell that formed the colony. These cytometric properties can then be used for subsequent analysis and/or sorting of the functionally-distinct subpopulations. During these studies, we will determine the optimal experimental parameters for indexed sorting of cells at high density for functional analysis. Specifically, we will maximize cell deposition density, develop surfaces suitable for identification of functionally-competent cells, optimize sorting conditions for precise indexed sorting and develop procedures for cell staining and sorting which are compatible with cell viability. An image analysis system will be used to identify functionally-competent cells and to determine their spatial locations. We will demonstrate the utility of this approach by applying it to the evaluation of probes for cells currently identified only by clonogenic assays (i.e., hematopoietic stem cells and cells killed by treatment with a chemotherapeutic agent). These data will be used in a hierarchial analysis program to identify cytometric properties that best describe the functionally-competent cells. The techniques we develop should be broadly applicable in studies aimed at the flow cytometric discrimination of a wide variety of functionally-competent cell subpopulations; particularly those present at low fequencies, such as malignant metastatic cells, infrequent transformed cells, and monoclonal antibody-producing cells.